Department of Cardiology, Zhongshan Hospital, Shanghai Institute of Cardiovascular Diseases, Fudan University, 180 Fenglin Road, Shanghai, 200032, China.
National Clinical Research Center for Interventional Medicine, Shanghai, China.
Eur J Med Res. 2023 Jul 29;28(1):262. doi: 10.1186/s40001-023-01237-w.
This study aims to develop a post-procedural risk prediction model for permanent pacemaker implantation (PPMI) in patients treated with transcatheter aortic valve replacement (TAVR).
336 patients undergoing TAVR at a single institution were included for model derivation. For primary analysis, multivariate logistic regression model was used to evaluate predictors and a risk score system was devised based on the prediction model. For secondary analysis, a Cox proportion hazard model was performed to assess characteristics associated with the time from TAVR to PPMI. The model was validated internally via bootstrap and externally using an independent cohort.
48 (14.3%) patients in the derivation set had PPMI after TAVR. Prior right bundle branch block (RBBB, OR: 10.46; p < 0.001), pre-procedural aortic valve area (AVA, OR: 1.41; p = 0.004) and post- to pre-procedural AVA ratio (OR: 1.72; p = 0.043) were identified as independent predictors for PPMI. AUC was 0.7 and 0.71 in the derivation and external validation set. Prior RBBB (HR: 5.07; p < 0.001), pre-procedural AVA (HR: 1.33; p = 0.001), post-procedural AVA to prosthetic nominal area ratio (HR: 0.02; p = 0.039) and post- to pre-procedural troponin-T difference (HR: 1.72; p = 0.017) are independently associated with time to PPMI.
The post-procedural prediction model achieved high discriminative power and accuracy for PPMI. The risk score system was constructed and validated, providing an accessible tool in clinical setting regarding the Chinese population.
本研究旨在为行经导管主动脉瓣置换术（TAVR）治疗的患者开发一种用于永久性心脏起搏器植入（PPMI）的术后风险预测模型。
在单个机构中，对 336 例接受 TAVR 的患者进行了模型推导。对于主要分析，使用多变量逻辑回归模型评估预测因子，并根据预测模型设计风险评分系统。对于次要分析，进行了 Cox 比例风险模型以评估与 TAVR 至 PPMI 时间相关的特征。该模型通过自举法进行内部验证，并使用独立队列进行外部验证。
在推导组中，有 48 例（14.3%）患者在 TAVR 后发生 PPMI。术前右束支阻滞（RBBB，OR：10.46；p<0.001）、术前主动脉瓣面积（AVA，OR：1.41；p=0.004）和术后至术前 AVA 比值（OR：1.72；p=0.043）被确定为 PPMI 的独立预测因子。AUC 在推导组和外部验证组中分别为 0.7 和 0.71。术前 RBBB（HR：5.07；p<0.001）、术前 AVA（HR：1.33；p=0.001）、术后 AVA 至人工瓣标称面积比值（HR：0.02；p=0.039）和术后至术前肌钙蛋白 T 差值（HR：1.72；p=0.017）与 PPMI 的时间独立相关。
术后预测模型对 PPMI 具有较高的区分能力和准确性。构建并验证了风险评分系统，为中国人群提供了一种在临床环境中易于使用的工具。
